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The SALSO algorithm is an efficient randomized greedy search method to find a point estimate for a random partition based on a loss function and posterior Monte Carlo samples. The algorithm is implemented for many loss functions, including the Binder loss and a generalization of the variation of information loss, both of which allow for unequal weights on the two types of clustering mistakes. Efficient implementations are also provided for Monte Carlo estimation of the posterior expected loss of a given clustering estimate. See Dahl, Johnson, Müller (2022) <doi:10.1080/10618600.2022.2069779>.
Version: | 0.3.35 |
Depends: | R (≥ 4.2.0) |
Published: | 2023-07-17 |
DOI: | 10.32614/CRAN.package.salso |
Author: | David B. Dahl salso author details |
Maintainer: | David B. Dahl <dahl at stat.byu.edu> |
BugReports: | https://github.com/dbdahl/salso/issues |
License: | MIT + file LICENSE | Apache License 2.0 |
URL: | https://github.com/dbdahl/salso |
NeedsCompilation: | yes |
SystemRequirements: | Cargo (Rust's package manager), rustc (>= 1.65) |
Materials: | NEWS INSTALL |
CRAN checks: | salso results |
Reference manual: | salso.pdf |
Package source: | salso_0.3.35.tar.gz |
Windows binaries: | r-devel: salso_0.3.35.zip, r-release: salso_0.3.35.zip, r-oldrel: salso_0.3.35.zip |
macOS binaries: | r-release (arm64): salso_0.3.35.tgz, r-oldrel (arm64): salso_0.3.35.tgz, r-release (x86_64): salso_0.3.35.tgz, r-oldrel (x86_64): salso_0.3.35.tgz |
Old sources: | salso archive |
Reverse imports: | AntMAN, batchmix, intRinsic, SANple |
Reverse suggests: | caviarpd |
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